Sometimes your algorithm need to collect or analyse data before applying heuristic to make a decision.This can be done by providing the computer with some data or by implementing an algorithm based on machine learning.However such an algorithm would have to investigate far too many possible moves and would quickly become too slow and too demanding in terms of memory resources in order to perform effectively.Tags: Online Cover Letter SubmissionEssay Questions Ancient EgyptArgumentative Essay PdfPlanning A Business MeetingDissertation Research Proposal ExampleAbi/Inform Complete + Dissertations & Theses Full TextMy Dreams Essay SpmTopics For Term PaperPlanning Your Essay StructureForensic Anthropology Dissertations
Can you explain how this could be the case with this scenario?
Heuristics can be mental shortcuts that ease the cognitive load of making a decision.
Examples of this method include using a rule of thumb, an educated guess, an intuitive judgement, guesstimate, stereotyping, profiling, or common sense.” “In computer science, a heuristic is a technique designed for solving a problem more quickly when classic methods are too slow, or for finding an approximate solution when classic methods fail to find any exact solution.
used by GPS systems and self-driving cars also use a heuristic approach to decide on the best route to go from A to Z (e.g. More advanced algorithms can also take into consideration a range of factors including the type of roads, the speed limits, live traffic data, etc. Artificial Intelligence algorithms based on machine learning where the computer builds up a knowledge base from previous experiences is another application of heuristic algorithms.
In this case the algorithm uses a self-maintained knowledge base to inform decisions and make “educated guesses” based on previous experiences.